Staff

Structure

This unit includes lectures, self-guided tutorials, labs, discussions, and drop-in sessions.

• Lectures: Tuesdays 10 AM, Wednesdays 11 AM, Chemistry Lecture Theatre 3
• Tutorials: Self-guided (1 hour), complete before each week’s lab.
• Labs: South Eveleigh Precinct, Thursday 9 am – 12 pm, Friday 10 am – 1 pm, 2 pm – 5 pm
• Discussion: Via Ed discussion, we usually respond the same day unless it is the weekend.
• Drop-in sessions: Scheduled as necessary (Zoom or in person). Email us to arrange a session.

Attendance

1. Lectures: Highly recommended but not compulsory. Lectures are recorded, capturing slides and audio only, which may miss important discussions.
2. Labs: Mandatory, 80% minimum attendance required. Attendance will be taken by QR code. If you miss a lab, you may attend another session that week – send us an email!
3. Tutorials: Self-guided (1 hour), complete before each week’s lab.

Assessments

Check Unit Outline

Biomedical Building

Credit: Michael Wheatland

Directions

Buses

Courtesy buses are available:

• The best option is to take the bus from Fisher Library to Redfern Station, then walk to the precinct (through the new station platform as “local traffic”).
• Alternatively, direct buses are available – but less frequent.

Driving

Free parking is available around Henderson Road, but it is extremely crowded. We do not recommend driving to the precinct.

Walking

Walking to the South Eveleigh Precinct takes about 20 minutes. However, you can save approximately 5 minutes by using Redfern station’s community access gates, where you don’t need to use an Opal card to get through.

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Statistics in Action

Modern science and decision-making are driven by data:

Why Statistics Matters?

Statistics empowers you to:

Real-world Applications

Source: NASA’s Global Temperature Index

Sports Analytics

The 10 highest-seeded players averaged 3.48 rounds won in the Australian Open since 2011, compared to just 3.03 at Wimbledon. Source: fivethirtyeight

Your Path Ahead

This course will develop your:

Lecture attendance options

In-person vs. online recordings

On-campus or online?

Choose the option that best suits your learning style and circumstances. If watching online, try to:

• Stay up to date with recordings to avoid falling behind
• Use Ed discussion board actively for questions
• Attend some lectures in person when possible for key topics

There is a strong positive correlation between lecture attendance and final grades – but it’s not the only factor. It may just be the case that students who attend lectures are more likely to keep up with the course material.

Put in the hours

• This is a 6 credit point unit, which means that you are expected to spend 120 – 150 hours in total, including exam prep time (~10 h per week)!
• Practice makes perfect. Tutorials and Labs help you apply the concepts you learn in lectures – complete all the exercises, and practice with the bonus questions provided.

Ask questions

• Ed is the best place to ask questions. We are way more responsive on Ed than on email.
• We are open to the use of AI tools (including LLMs like ChatGPT) to help you answer questions about code… but don’t use them to cheat yourself out of learning.
• We have drop-in sessions, where you can jump in and have a chat on Zoom. We will announce the schedule on Ed.

By the end of this course, we want you to be able to:

• LO1 demonstrate proficiency in designing sample schemes and analysing data from them using R.
• LO2 describe and identify the basic features of an experimental design: replicate, treatment structure and blocking structure.
• LO3 demonstrate proficiency in the use or the statistical programming language R to apply an ANOVA and fit regression models to experimental data.
• LO4 demonstrate proficiency in the use or the statistical programming language R to use multivariate methods to find patterns in data.
• LO5 interpret the output and understand conceptually how its derived of a regression, ANOVA and multivariate analysis that have been calculated by R.
• LO6 write statistical and modelling results as part of a scientific report.
• LO7 appraise the validity of statistical analyses used publications.